Exelon will present a production-scale AI implementation designed to proactively identify high-risk underground residential distribution (URD) cables and improve maintenance planning across multiple operating companies. The session will cover how predictive models were built using outage history, cable attributes, and environmental conditions to improve failure prediction performance and support reliability-focused decision making. Attendees will also learn about operational deployment strategies, planner-friendly dashboards, and methods for measuring the business value of predictive analytics.

Session Takeaways:
• How to build AI-driven URD failure prediction models
• Lessons learned deploying predictive analytics across utilities
• Approaches for measuring operational and financial benefits
• Best practices for integrating AI into maintenance workflows